The outcome variable for this study was the prevalence of the eye disease of interest (DR, glaucoma, cataracts). Potential risk covariates were then identified based on previously published literature and their availability through the VEHSS at the county level. In this study, the risk covariates included geographic region and race/ethnicity, which were categorized according to the predefined parameters of the VEHSS. Since the VEHSS database provides disease data based on Medicare claims, other potential risk covariates such as commercial medical insurance or Medicaid were not included, which was a limitation of the VEHSS database. In addition, disease prevalence and cataract surgery data were included in the analyses from 2014–2019, while data pertaining to disease prevalences based on race from the IRIS registry were assessed from 2016–2019 due to data availability.

Additional risk covariates that were considered for inclusion were the median household income by county, prevalence of persons in poverty, rate of income inequality, level of education completion, number of medical providers by county, and prevalence of uninsured persons per county. However, these ultimately could not be included in the data analysis as they were not variables included in the VEHSS system which defined the prevalence of the eye disease of interest. The potential risk covariates were nevertheless considered to be relevant and subsequently assessed through literature reviews and publicly available databases.

All statistical analyses were performed with GraphPad Prism version 10.0.3 for Mac (GraphPad Software, Boston, Massachusetts United States, https://www.graphpad.com/). Secondary data that compared more than two groups utilized either a one-way ANOVA or two-way ANOVA followed by Tukey’s or Sidak’s correction for multiple comparisons. Bartlett’s test and Brown-Forsythe’s test were used to assess variances across groups in our ANOVAs. Secondary data from two groups were analyzed with two-tailed unpaired t-tests and were checked for normality using the D’Agostino-Pearson omnibus test (K2). An F-test was used to compare variances across groups in t-tests. Where appropriate, data are presented as mean ± standard error. Data are also shown as mean ± standard deviation or mean ± upper/lower confidence limits. Standard deviation was calculated based on the sample size (n) and confidence intervals retrieved from the VEHSS database.

The final analysis determined disease prevalence in New York State, Erie County, Monroe County, and at the national level separately. In 2022, New York State had a population of 19,677,151 individuals with a population density as of 2020 at 428.7 persons per square mile. In contrast, Erie and Monroe County had populations of 950,312 and 752,035, respectively. The population density in Erie County was determined to be 915.1 while that of Monroe County was 1,156 persons per square mile (Table 1). New York State and Western New York racial and ethnic demographics and life expectancy based on race are shown in Tables 2 and 3. Data for economic and educational metrics are seen in Tables 4 and 5. Moreover, Erie County faces a greater primary care physician (PCP) shortage with 1 PCP per 1,250 individuals compared to Monroe County, which has 1 PCP for 910 individuals (Table 6). Monroe County had a slightly higher prevalence of people without health insurance at 10.8% compared to Erie County at 9.7% (Table 7).

Analyses of variance were calculated to show the effects of the covariates, or independent variables, on disease prevalence. These covariates included geographic region, gender, race/ethnicity, and Medicare coverage. With the variability of the differences in population characteristics between the geographic regions of New York, these covariates could allow insight into what factors were associated with the diversity and trends of disease burden in specific regions. Many of these were significantly associated with disease burden and labeled as risk factors, while others were shown to have no significant association with the disease of interest.

Potential risk covariates included in the analysis and additional relevant variables that were examined through the initial literature review and publicly available data were all assessed in comparison to the disease of interest. These additional relevant variables include the number of physicians, median household income, and level of education completion from 2017–2021 (Tables 4, 5, and 6). However, as these are not included in the VEHSS system or IRIS registry, which defines the prevalence of disease, these were not included in the final data analysis.

In our examination of cataract prevalence (assessed through Medicare data), a statistically significant interaction was observed, highlighting the joint impact of geographical location and calendar year on prevalence [F (15, 190266376) = 12.80, p < 0.0001]. Despite Monroe County having a significantly lower overall rate of cataract prevalence, there is a temporal increase in the percentage of individuals developing cataracts (Figure 1).

A statistically significant interaction was also observed during the analysis of glaucoma prevalence (assessed through Medicare data), revealing the effect of both geographical location and calendar year on prevalence [F (15, 190266376) = 2.867, p < 0.001]. Both Erie and Monroe County were found to have significantly lower overall rates of glaucoma prevalence when compared to the overall average of New York State (Figure 2).

In our evaluation of diabetic eye disease prevalence (assessed through Medicare data), a statistically significant interaction was once again observed between the impact of geographical location and calendar year on prevalence [F (15, 190266376) = 14.92, p < 0.0001]. Though there is a temporal decrease in prevalence amongst all groups, New York State has a significantly higher prevalence than the national average (Figure 3).

In our examination of cataract prevalence by race (assessed through IRIS registry state-wide data), there was no statistically significant interaction observed between self-identified race/ethnicity and year [F (5, 18) = 0.7651, p = 0.587]. Though there was no statistically significant outcome, there was an increase in the percentage of individuals with cataract disease over time (Figure 4).

For glaucoma prevalence by race (assessed through IRIS registry state-wide data), a statistically significant interaction was observed, highlighting the interaction of self-identified race/ethnicity with calendar year [F (5, 18) = 11.89, p < 0.0001]. Further, Black, non-Hispanics have significantly higher rates of prevalence than any other race in New York State (Figure 5).

In our analysis of diabetic eye disease prevalence by race (assessed through IRIS registry state-wide data), a statistically significant interaction was observed, revealing the joint impact of self-identified race/ethnicity and calendar year [F (5, 18) = 36.75, p < 0.0001]. Individuals identifying as Native American, Black, non-Hispanic, Asian, and Hispanic, any race have significantly higher disease burden in New York State (Figure 6).

A statistically significant interaction was observed in the utilization of eye exams assessed through Medicare data, highlighting the dual impact of geographical location and calendar year [F (15, 190266376) = 18.85, p < 0.0001]. Both Erie and Monroe County have significantly lower overall rates of eye exams when compared to the overall average of New York State (Figure 7).

In our analysis of cataract surgery (assessed through Medicare data), a statistically significant interaction was measured, highlighting the joint impact of geographical location and calendar year [F (20, 67178570) = 4.854, p < 0.0001]. Although Erie and Monroe County have similar rates to New York State, the percentages of cataract surgery in these areas are significantly lower than both the national rate and high-volume states such as Florida (Figure 8).

The incidence of cataracts is on an upward trajectory, as illustrated in Figure 1. Given the escalating median age of our population, this pattern is anticipated to persist. By 2025, projections indicate that over 40 million individuals will be affected by cataracts due to the aging demographic. Consequently, healthcare professionals must be equipped to assess, diagnose, and provide surgical solutions to prevent visual impairment and vision loss. Interestingly, while New York State demonstrates higher cataract prevalence rates compared to the national average, its rate of cataract surgeries remains below the national average. This disparity is mirrored in our local regions of Erie and Monroe County. Despite the absence of significant racial or ethnic disparities in cataract prevalence within these counties, the mounting challenge posed by an aging demographic suggests that the existing ophthalmology workforce might face constraints in addressing this surge effectively (Table 6) [29]. Moreover, the lack of meaningful increase in residency programs for all medical specialties, including ophthalmology, will exacerbate the current burden of lack of primary and specialist care.

While glaucoma prevalence rates in New York State surpass the national average, the rate of increase is slower than that seen in cataract disease. However, upon further inspection of glaucoma prevalence in Western New York, there is a concerning picture of potential gaps and underutilization in eye care services. Specifically, both Erie and Monroe County consistently report lower rates of glaucoma prevalence when compared with the broader New York State averages. Such findings raise concerns for possible underdiagnosis or limited accessibility to essential eye care services within these specific regions. Our data on eye care services, specifically eye exams, further supports this notion. Although New York State surpasses the national average of percentage of eye exams, both Erie and Monroe County fall significantly below the state’s average. This reduced utilization of routine eye examinations could contribute to the underdiagnosis of ocular pathology and subsequent lower prevalence rates found in our analysis. This concern is further compounded by the disproportionate disease burden faced by certain racial and ethnic groups in New York State. Notably, Black, non-Hispanic populations in New York State experience significantly higher rates of glaucoma prevalence compared to their counterparts from other racial backgrounds. This disparity highlights potential systemic challenges that are prevalent throughout the United States such as lack of healthcare access, transportation, and resources that may be inhibiting these communities from accessing timely and essential eye care.

In our comprehensive analysis of diabetic eye disease within Western New York, disparities in eye care reaffirmed the urgency for rethinking access and delivery to eye care. In our examination of prevalence of diabetic eye disease, the overall New York State prevalence was significantly higher than the national average. Again, as with cataract and glaucoma prevalence, both Erie and Monroe County exhibited lower disease prevalence rates when compared to the state average. This concerning trend is further complicated by the racial and ethnic disparities revealed in our analysis. Specifically, Native American, Black, non-Hispanic, Asian, and Hispanic individuals in New York State shoulder a disproportionately higher burden of diabetic eye disease.

Such significant differences in eye disease prevalence alongside racial and ethnic disparities suggest intricate intersections of race, ethnicity, and systemic factors that amplify the disease’s impact on our local communities. Furthermore, consistently lower rates of eye care utilization in both Erie and Monroe County when compared to New York State’s broader averages signal potential barriers to early detection and intervention in these regions. Addressing these disparities demands a multifaceted approach such as integrating enhanced screening initiatives, increasing emphasis on preventative care, promoting education and community outreach, and tailoring interventions to mitigate the profound impact of eye disease on vulnerable populations.

Minority and disadvantaged populations face higher susceptibility to developing DR, glaucoma, and cataract disease, leading to poorer visual health outcomes. Oftentimes, disadvantaged populations lack the access and resources to attend regular eye exams, resulting in individuals presenting with more severe stages of these diseases and worse outcomes.

This vulnerability is further increased by inadequate screening in these high-risk groups. Less than half of all United States adults adhere to guideline-recommended eye screenings, with racial and ethnic minorities being screened less often than white patients [30, 31]. Evidence regarding the importance of timely detection and screening for PDR and DME was shown years ago in the DR Study and the Early Treatment of Diabetic Study [32, 33]. However, delayed diagnosis still remains a concern among Black and Hispanic patients with diabetes, who are more likely to present at advanced stages of DR, which may lead to poorer visual outcomes [8].

For instance, Hispanic and Latino Americans have higher risks of clinically significant macular edema (CSME) [34], with prevalence in the Beaver Dam Eye Study being twice as high as that of the White population [35–37]. The Veterans Affairs Diabetes Trial yielded similar results, with 15.6% of African Americans having CSME compared to 6.3% of non-Hispanic Whites [38]. The underlying causes of these disparities remain complex with studies pointing to differences in pathogenesis, genetic susceptibility to CSME, and also delayed detection and screening.

Individuals with lower education and those who lack insurance are less likely to undergo screening. In fact, those without health insurance are twice as likely to have not seen a doctor in the previous year [9, 39]. Despite recommendations for routine annual dilated exams, only 33–68% of individuals of adults with diabetes follow-up for their yearly exams, and these screening rates are even lower in Blacks and Latinos [40].

Hence it is critical to address the barriers to eye screening and eye care utilization faced by minority populations, including disparities in access, education, and awareness in order to improve visual health outcomes and reduce the burden of ocular disease in our communities of color.

Insufficient patient education by healthcare providers poses a significant barrier to the utilization of eye care services [41, 42]. Patient education is particularly important in chronic disease management. For instance, diabetic patients with a longer duration of disease are more likely to develop DR. The rate of development of DR in a patient with no previous retinopathy on exam one year prior is reported to be between 5 and 10%. However, studies such as LALES and Proyecto VER have shown that 18% of Hispanic patients with diabetes lasting over 15 years developed PDR [14, 15].

In addition to the duration of diabetes, there are several modifiable risk factors that should be closely monitored by the primary care team, such as hyperglycemia, hyperlipidemia, hypertension, and higher total serum cholesterol levels. Regular monitoring of hemoglobin A1c (HbA1c) and blood pressure readings is essential in managing these associated comorbidities [43–46]. This highlights the importance of interprofessional collaboration and the role of primary care providers in screening for eye disease [47]. An initial strategy to improve follow-up and strengthen the physician-patient relationship is to enhance cultural competency among providers. Cultural competency can help increase understanding and respect for other cultures, races, and languages to deliver the best care for all individuals. This initiative may help create a more inclusive healthcare environment, which can address racial disparities and increase the number of ethnic minority patients who are screened [48, 49].

Educating primary care providers on screening guidelines for DR may indirectly contribute to patient education and health literacy [50]. By raising awareness among both patients and primary care providers, the significance of regular screenings for chronic eye disease can be emphasized, ultimately leading to improved eye care utilization and better eye care outcomes.

Public health structures play a crucial role in addressing health disparities and improving access to eye care services. These structures can be leveraged to implement interventions and policies that address the specific needs of marginalized populations. One approach to target high risk groups with lower rates of follow-up is to integrate eye care services into existing public health programs. This can involve collaborations between eye care professionals, primary care providers, medical schools, and public health agencies to establish comprehensive screening programs and referral systems [51]. By incorporating eye screenings into routine health check-ups, especially for high-risk populations, we can look to increase detection and timely intervention for ocular diseases.

Other initiatives such as mobile clinics and telehealth initiatives can be utilized to overcome geographical and logistical barriers. These outreach initiatives may better serve individuals in remote areas and those with limited physical mobility or lack of transportation [52]. Additional interventions may include the development of targeted education campaigns, which can focus on raising health literacy in vulnerable communities [53]. Subject matter may include the importance of regular eye exams, dispelling common misconceptions surrounding eye health, and the promotion of culturally sensitive health literacy materials [54]. Increasing eye care knowledge may empower individuals to prioritize their eye health, leading to improved long term outcomes for communities. Through education and prevention, poor prognoses of chronic preventable eye disease in high-risk groups (regardless of geographic region) may begin to change.

The global population is projected to increase significantly from 7.3 billion in 2015 to 9.7 billion by 2050, with a larger proportion of older individuals by 2050. Within the last decade, the United States population has also increased in size, age, and diversity. Within New York State and Western New York, the growing diversity of the population has highlighted the long-standing disparities in access to eye care and subsequent poor visual outcomes in minority populations. As the risk of eye conditions and prevalence of visual impairment rises with age, it is crucial to address the growing burden of ocular diseases [55]. Given the demographic shifts, the prevalence of ocular diseases is evident and will continue to rise and disproportionately affect minority communities unless proactive measures are taken.

To address racial health disparities in ocular diseases such as DR, glaucoma, and cataracts, it is crucial to increase awareness, promote screening, and provide support and encouragement. Additionally, conducting research on disease prevalence, especially in growing and diverse communities, while considering the social determinants of health model and modifiable risk factors is essential for guiding public health education and interventions to improve clinical management of ocular diseases. To further reduce disparities, research efforts should continue to concentrate on identifying and addressing specific factors that hinder access to eye care services. It is equally important to develop and implement strategies that enhance the overall health literacy of these communities at high risk. By increasing health literacy, individuals will gain skills necessary to recognize the importance of regular eye exams and may be more likely to seek care when needed.

Population-based studies that incorporate both individual and environmental data can help further investigate the impact of race and ethnicity on the prevalence of ocular diseases. Ensuring access to healthcare services and implementing public health policies that prioritize adequate care are fundamental in preventing blindness in our patients.